The Japanese are meticulous record keepers.. they know how many shots someone got and how long after they died, unlike the criminal system in USA and the UK who fudge data and in some cases remove it entirely when it suits them, remember the vaccine card status?.. that was on a web based data system so they could check if you were up to date.. it’s how the NHS sent reminders, do where did that data go.. it got wiped when they realised it would act as evidence that these shots were not safe and effective ..just dangerous and deadly.
You can't tell how toxic the lots are based on the percentage of deaths per batch. The percentage is not even adjusted for age or person-days. For example first doses have a much lower percentage of deaths per dose than later doses, because people typically spent less than 6 weeks with the first dose as their most recent dose. The deaths were only counted under the most recent dose before death and not under all doses.
Out of the cities included in the Japanese FOI data, I believe the only city that has individual record-level data available is Koganei, which includes about 140,000 people: https://medicalfacts.info/vdeath.rb.
The age column in the Koganei file shows the age in May 2025. The average age is about 59 for all lots but 65 for FM3289.
In the Koganei data virtually all doses of FM3289 are third doses. The average person-days per dose is about 31 for first doses but 483 for third doses, which causes batches administered for third doses to have higher deaths per dose than batches administered for first doses:
Albert, I get what you are doing but you going to have to figure out how to put names to the data. It’s like the people in the trial who were injured and then ignored. The throttled cases are people an none of them are aware that they have been hidden. Do you have any lists of people with vares ids that have been throttled or deleted? Once you personalize the data then people will want to care.
The Japanese are meticulous record keepers.. they know how many shots someone got and how long after they died, unlike the criminal system in USA and the UK who fudge data and in some cases remove it entirely when it suits them, remember the vaccine card status?.. that was on a web based data system so they could check if you were up to date.. it’s how the NHS sent reminders, do where did that data go.. it got wiped when they realised it would act as evidence that these shots were not safe and effective ..just dangerous and deadly.
Deliberate mis-filings. "Mistakes Were Not Made." Conspiracy to commit fraud, times tens of thousands of filings.
If only we had The Eagle in charge of a criminal investigation unit of a functional FBI.
They would all be making big rocks into little rocks for the next 20 years.
You can't tell how toxic the lots are based on the percentage of deaths per batch. The percentage is not even adjusted for age or person-days. For example first doses have a much lower percentage of deaths per dose than later doses, because people typically spent less than 6 weeks with the first dose as their most recent dose. The deaths were only counted under the most recent dose before death and not under all doses.
Out of the cities included in the Japanese FOI data, I believe the only city that has individual record-level data available is Koganei, which includes about 140,000 people: https://medicalfacts.info/vdeath.rb.
The age column in the Koganei file shows the age in May 2025. The average age is about 59 for all lots but 65 for FM3289.
In the Koganei data virtually all doses of FM3289 are third doses. The average person-days per dose is about 31 for first doses but 483 for third doses, which causes batches administered for third doses to have higher deaths per dose than batches administered for first doses:
t=fread("https://fujikawa.org/pub/jp132101_Koganei-Tokyo_all.csv",fill=T)
l=t[,.(.I,dose=rep(1:7,each=.N),dead=date_death)]
l$date=t[,`class<-`(unlist(.SD,,F),"Date"),.SDcols=patterns("^date_lot")]
l=merge(l,l[dose>1,.(I,dose=dose-1,nextdate=date)],all=T)
l[,enddate:=pmin(nextdate,dead,as.Date("2025-3-31"),na.rm=T)]
a=l[!is.na(date),.(pdays=sum(as.integer(enddate-date+1)),doses=.N),dose]
round(a[,pdaysperdose:=pdays/doses])
# dose pdays doses pdaysperdose
# 1 2733031 88843 31
# 2 32091654 88330 363
# 3 36775052 76179 483
# 4 21515895 51090 421
# 5 11850455 32494 365
# 6 5571348 20340 274
# 7 6999546 13644 513
I am curious to see what happens when you get lot numbers of the self amplifying Covid shots Japan is pushing out.
That’s a scary thing, indeed!
Albert, I get what you are doing but you going to have to figure out how to put names to the data. It’s like the people in the trial who were injured and then ignored. The throttled cases are people an none of them are aware that they have been hidden. Do you have any lists of people with vares ids that have been throttled or deleted? Once you personalize the data then people will want to care.